LMD和支持向量机相结合的齿轮毂故障诊断方法

陈鹏飞; 陈卫; 高星伟; 杜炜; 张海涛

doi:10.13433/j.cnki.1003-8728.2015.1023

LMD和支持向量机相结合的齿轮毂故障诊断方法

doi: 10.13433/j.cnki.1003-8728.2015.1023

1.
空军工程大学航空航天工程学院, 西安 710038

基金项目:

国家自然科学基金项目(51175509,51405028)资助

详细信息

作者简介:
陈鹏飞(1990-),硕士研究生,研究方向为动力装置结构、强度与振动,543122109@qq.com

通讯作者:
陈卫,副教授,硕士,chen_wz@sina.com

计量
- 文章访问数: 185
- HTML全文浏览量: 34
- PDF下载量: 9
- 被引次数: 0
出版历程
- 收稿日期: 2014-07-08
- 刊出日期: 2015-10-05

Fault Diagnosis of Gear Hub Based on LMD and Support Vector Machine

1.
Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi'an 710038, China

摘要

摘要: 局部均值分解(LMD)作为一种新的自适应时频分析方法,在故障诊断领域展现了良好的应用前景。根据某型航空发动机减速器一级齿轮毂出现裂纹故障时其振动信号会产生调制现象的特点,提出了基于LMD和支持向量机(SVM)的某型航空发动机减速器一级齿轮毂裂纹故障诊断方法。对某型航空发动机进行振动测试获取其振动样本数据,利用LMD提取故障样本数据的故障特征信息、构造特征向量,并将其作为SVM的输入特征参数,成功建立了针对目标故障的故障诊断模型。对一级齿轮毂工作状态的分析结果表明了该方法的有效性。
- 故障诊断 /
- 局部均值分解 /
- 支持向量机 /
- 齿轮毂
Abstract: As a new kind of self-adaptation time-frequency analysis approach, the local mean decomposition(LMD) shows a good application prospect in fault detection. According to the fact that the characteristics of vibration signal can be modulated when the crack fault exists on the gear hub of the reducer in an aero engine, we spropose a fault detection method based on LMD and support vector machine(SVM). Firstly, vibration sample data acquired through vibration tests performed in the aero engine. Then the fault information of fault gear hub was extracted by LMD to construct feature vectors. Eventually, taking the feature vectors as the input parameter of SVM, a fault detection model towards the target fault was successfully established. The analysis results demonstrate the effectiveness of the proposed method.
- aircraft engines /
- design of experiments /
- efficiency /
- eigenvalues and eigenfunctions

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参考文献(13)

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